Biomedical subjects

Kimberly A Watson

Publications and source records attributed to Kimberly A Watson.

3 recordsLinked to original sources

PubMed2006

Preliminary X-ray diffraction analysis of YcdB from Escherichia coli: a novel haem-containing and Tat-secreted periplasmic protein with a potential role in iron transport.

YcdB is a periplasmic haem-containing protein from Escherichia coli that has a potential role in iron transport. It is currently the only reported haem-containing Tat-secreted substrate. Here, the overexpression, purification, crystallization and structure determination at 2.0 A resolution are reported for the apo form of the protein. The apo-YcdB structure resembles those of members of the haem-dependent peroxidase family and thus confirms that YcdB is also a member of this family. Haem-soaking experiments with preformed apo-YcdB crystals have been optimized to successfully generate haem-containing YcdB crystals that diffract to 2.9 A. Completion of model building and structure refinement are under way.

Biological Transport↗

PubMed2005

Kinetic and crystallographic studies of glucopyranose spirohydantoin and glucopyranosylamine analogs inhibitors of glycogen phosphorylase.

Glycogen phosphorylase (GP) is currently exploited as a target for inhibition of hepatic glycogenolysis under high glucose conditions. Spirohydantoin of glucopyranose and N-acetyl-beta-D-glucopyranosylamine have been identified as the most potent inhibitors of GP that bind at the catalytic site. Four spirohydantoin and three beta-D-glucopyranosylamine analogs have been designed, synthesized and tested for inhibition of GP in kinetic experiments. Depending on the functional group introduced, the K(i) values varied from 16.5 microM to 1200 microM. In order to rationalize the kinetic results, we determined the crystal structures of the analogs in complex with GP. All the inhibitors bound at the catalytic site of the enzyme, by making direct and water-mediated hydrogen bonds with the protein and by inducing minor movements of the side chains of Asp283 and Asn284, of the 280s loop that blocks access of the substrate glycogen to the catalytic site, and changes in the water structure in the vicinity of the site. The differences observed in the Ki values of the analogs can be interpreted in terms of variations in hydrogen bonding and van der Waals interactions, desolvation effects, ligand conformational entropy, and displacement of water molecules on ligand binding to the catalytic site.

Crystallography, X-Ray↗

PubMed2002

New approach to pharmacophore mapping and QSAR analysis using inductive logic programming. Application to thermolysin inhibitors and glycogen phosphorylase B inhibitors.

A key problem in QSAR is the selection of appropriate descriptors to form accurate regression equations for the compounds under study. Inductive logic programming (ILP) algorithms are a class of machine-learning algorithms that have been successfully applied to a number of SAR problems. Unlike other QSAR methods, which use attributes to describe chemical structure, ILP uses relations. This gives ILP the advantages of not requiring explicit superimposition of individual compounds in a dataset, of dealing naturally with multiple conformations, and of using a language much closer to that used normally by chemists. We unify ILP and standard regression techniques to give a QSAR method that has the strength of ILP at describing steric structure with the familiarity and power of regression methods. Complex pharmacophores, correlating with activity, were identified and used as new indicator variables, along with the comparative molecular field analysis (CoMFA) prediction, to form predictive regression equations. We compared the formation of 3D-QSARs using standard CoMFA with the use of ILP on the well-studied thermolysin zinc protease inhibitor dataset and a glycogen phosphorylase inhibitor dataset. In each case the addition of ILP variables produced statistically better results (P < 0.01 for thermolysin and P < 0.05 for GP datasets) than the CoMFA analysis. Moreover, the new ILP variables were not found to increase the complexity of the final QSAR equations and gave possible insight into the binding mechanism of the ligand-protein complex under study.

Algorithms↗